Self-renewal induced efficiently, safely, and effective therapeutically with one regulatable gene in a human somatic progenitor cell
Bibliographic record
Abstract
In the field of induced potency and fate reprogramming, it remains unclear what the best starting cell might be and to what extent a cell need be transported back to a more primitive state for translational purposes. Reprogramming a committed cell back to pluripotence to then instruct it toward a particular specialized cell type is demanding and may increase risks of neoplasia and undesired cell types. Precursor/progenitor cells from the organ of therapeutic concern typically lack only one critical attribute--the capacity for sustained self-renewal. We speculated that this could be induced in a regulatable manner such that cells proliferate only in vitro and differentiate in vivo without the need for promoting pluripotence or specifying lineage identity. As proof-of-concept, we generated and tested the efficiency, safety, engraftability, and therapeutic utility of "induced conditional self-renewing progenitor (ICSP) cells" derived from the human central nervous system (CNS); we conditionally induced self-renewal efficiently within neural progenitors solely by introducing v-myc tightly regulated by a tetracycline (Tet)-on gene expression system. Tet in the culture medium activated myc transcription and translation, allowing efficient expansion of homogeneous, clonal, karyotypically normal human CNS precursors ex vivo; in vivo, where Tet was absent, myc was not expressed, and self-renewal was entirely inactivated (as was tumorigenic potential). Cell proliferation ceased, and differentiation into electrophysiologically active neurons and other CNS cell types in vivo ensued upon transplantation into rats, both during development and after adult injury--with functional improvement and without neoplasia, overgrowth, deformation, emergence of non-neural cell types, phenotypic or genomic instability, or need for immunosuppression. This strategy of inducing self-renewal might be applied to progenitors from other organs and may prove to be a safe, effective, efficient, and practical method for optimizing insights gained from the ability to reprogram cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".